Unlocking the Power of Data: How Big Data Applications are Transforming Industries

 Unlocking the Power of Data: How Big Data Applications are Transforming Industries 



HOW BIG DATA IS MAJORLY CHANGING INDUSTRIES

Data now has a central position in organisations of all sizes, in all areas of the public and commercial sectors, and across all industries. The advent of the cloud, the widespread usage of the Internet, and most recently the sensors, gadgets, and networks that make up the Internet of Things (IoT) are all contributing reasons.vvvv


Because of the accessibility of large volume, high velocity data to organisations from a variety of sources, big data analytics are increasingly necessary to compete in the market. But it's important to remember that using the power of Big Data requires more than just purchasing the appropriate tools. Without a comprehensive data strategy, organisations will struggle to make sense of all that data and run the danger of falling behind their more prepared rivals.


Here's a look at how business at all levels is being transformed by Big Data analytics technologies.


Before we go in, let's be clear that the word "data analytics" has been used by numerous organisations, BI suppliers, and magazines to denote a practically limitless range of tasks. The issue of "how are businesses using data analytics" is difficult to answer as a result.


By industry, company size, and access to resources, there are significant differences in how businesses use data analytics in their operations. Examples of business data analytics include financial services firms that use data analytics to examine expenditure trends in order to spot and stop fraud.


To improve hiring practises and evaluate employee performance, human resource departments are using data analytics.


Additionally, internet retailers employ data analytics to monitor email marketing effectiveness, analyse web traffic, and create tailored ad campaigns. Beyond releasing the economic value from a company's diverse array of data sources, data analytics is also used to improve the world.


For instance, the World Economic Forum claims that data is crucial in the fight against climate change. It aids in the quantification of emissions from oil and gas fields, the identification of damaging supply chain operations, and the monitoring of leaks, pollutants, and abnormalities at particular places.



Numerous approaches exist for how big data applications are changing industry. Here are a few instances:


1.Healthcare: By enhancing patient outcomes, lowering costs, and boosting efficiency, big data analytics are revolutionising the healthcare sector. Healthcare professionals can use big data analytics to identify patient health concerns, examine patient data to create better therapies, and enhance patient outcomes.


2. Retail: To personalise the shopping experience for customers, forecast customer behaviour, optimise pricing and inventory, and enhance supply chain management, retail organisations are turning to big data analytics. Online merchants, for instance, can use data analytics to suggest products to customers based on their previous browsing and purchasing behaviour.


3. Finance: The financial sector is being transformed by big data analytics, which has improved risk management, fraud detection, and customer service. Banks and other financial institutions use big data to analyse consumer information and offer individualised financial goods and services.


4. Manufacturing: By enhancing production efficiency, lowering costs, and improving product quality, big data analytics is revolutionising the manufacturing sector. Big data analytics can be used by manufacturers to streamline their supply chains, enhance their production techniques, and create new goods.


5. Transportation: Big data analytics is revolutionising the transportation sector by enhancing safety, cutting costs, and boosting productivity. Big data analytics can assist transportation companies enhance their operations, optimise their routes, and use less fuel.


Big data applications are, in general, altering industries by giving information about consumer behaviour, enhancing operational effectiveness, and cutting costs. We may anticipate even more industry-transforming shifts as more businesses employ big data analytics.




๐Ÿ‘Anushree Shinde

Anushree  Shinde[ MBA] 

Business Analyst

10BestInCity.com Venture

+91 9011586711

anushree@10bestincity.com

10bestincityanushree@gmail.com

www.10BestInCity.com 

Linktree:https://linktr.ee/anushreeas?utm_source=linktree_profile_share

LinkedIn: https://www.linkedin.com/company/92521776/admin/

Facebook: https://shorturl.at/hsx29

Instagram: https://www.instagram.com/10bestincity/

Pinterest: https://in.pinterest.com/shekharcapt/best-in-city/

Youtube: https://www.youtube.com/@10BestInCity

Email: info@10bestincity

https://www.portrait-business-woman.com/2023/05/anushree-shinde.html


https://www.anxietyattak.com/2023/05/unlocking-power-of-data-how-big-data.html 

#UnlockingThePowerOfData ,  #BigDataApplications

, #TransformingIndustries ,  #DataDrivenInsights

,#DataAnalytics ,  #MachineLearning

,#ArtificialIntelligence , #DigitalTransformation

,#InnovationThroughData , #DataScience

,#BusinessIntelligence , #PredictiveAnalytics

,#DataVisualization , #CloudComputing

,#DataSecurity , #InternetOfThings

,#Industry4.0 , #SmartCities

,#DataManagement , #BigDataStrategy

Time Series Analysis Analyzing Data that Varies Over Time

Time Series Analysis: 

Analyzing Data that Varies Over Time



Time series analysis is a statistical technique used to analyze data that varies over time. It involves analyzing data points that are collected at regular intervals over a specific period, such as hourly, daily, weekly, monthly, or yearly. Time series data is used in various fields, such as finance, economics, engineering, and the social sciences, to understand patterns and trends in the data.


The goal of time series analysis is to identify the underlying structure and patterns in the data and make predictions about future values. The analysis involves examining the time series data for trends, seasonal patterns, cycles, and irregular fluctuations. The time series data can also be decomposed into its various components to better understand the underlying patterns and trends.


Some common applications of time series analysis include forecasting future trends in financial markets, predicting weather patterns, analyzing economic data, and modeling sales patterns for businesses.


There are various steps you can follow to analyze data that changes over time, like time series data. 


1. Collect the data- To begin the analysis of time series data, it is essential to collect the relevant data points over a specific period. The collection process may involve gathering data at regular intervals, which can be hourly or daily, or at irregular intervals, depending on the type of data being analyzed.


2. Clean and preprocess the data- To begin the analysis of time series data, it is essential to collect the relevant data points over a specific period. The collection process may involve gathering data at regular intervals, which can be hourly or daily, or at irregular intervals, depending on the type of data being analyzed.


3. Visualize the data- To gain deeper insights into the time series data and detect patterns and trends, it is beneficial to represent the data visually using charts and graphs. This may entail plotting the data over time, analyzing the distribution and variation of the data, and using other graphical techniques to visualize the data. Visualizing the data can provide a clearer understanding of the underlying patterns and trends, making it easier to draw meaningful conclusions and make accurate predictions.


4. Visualize the data- After visualizing the data, the next step is to analyze it using statistical methods and models. This might include conducting trend analysis, detecting seasonal patterns, and applying time series models such as ARIMA to generate predictions. By performing these analyses, you can gain deeper insights into the behavior of the time series data, identify trends and patterns, and make accurate predictions about future values.


5. Interpret the results- Once the data has been analyzed, it is crucial to interpret the results to draw meaningful conclusions. This may entail recognizing patterns, making forecasts about future behavior, and utilizing the insights gleaned from the analysis to inform decision-making. It is important to accurately interpret the findings to make informed decisions based on the data.


To analyze data that changes over time, it is necessary to engage in a multi-step process that includes collecting, preprocessing, visualizing, analyzing, and interpreting the data. This process employs statistical techniques and models to identify patterns and trends in the data. The analysis requires a combination of skills and tools to effectively extract insights and draw meaningful conclusions from the data.



๐Ÿ‘Anushree Shinde [ MBA] 

Business Analyst

10BestInCity.com Venture

anushree@10bestincity.com

10bestincityanushree@gmail.com

www.10BestInCity.com 

Linktree:

https://linktr.ee/anushreeas?utm_source=linktree_profile_share

LinkedIn: 

https://www.linkedin.com/company/92521776/admin/

Facebook: 

https://shorturl.at/hsx29

Instagram: 

https://www.instagram.com/10bestincity/

Pinterest: 

https://in.pinterest.com/shekharcapt/best-in-city/

Youtube: 

https://www.youtube.com/@10BestInCity

Email: info@10bestincity

https://www.portrait-business-woman.com/2023/05/anushree-shinde.html



#TimeSeriesAnalysis,  #DataAnalysis, #DataScience,  #StatisticalAnalysis, #TrendAnalysis, #Forecasting, #DataVisualization, #TimeSeriesModels, #ARIMA , #SpectralAnalysis, #DataTrends , #DataPatterns , #DataInsights , #DecisionMaking , #DataDriven , #BigData, #Analytics , #BusinessIntelligence , #MachineLearning , #ArtificialIntelligence ,#PredictiveModeling

Social Media Analytics is an Essential Part of SMM Social media marketing

Social Media Analytics is an Essential Part of SMM Social media marketing?

Make Way for the Future of SMM: Unleash the Power of Social Media Analytics

Social media analytics (SMA) is shaking up the marketing world with its potential to unlock insights that can inform decision-making and drive business growth. By leveraging data from social networks, SMA can give marketers an unprecedented view into their customers’ behaviors, interests, and preferences. But this power comes with a caveat: it’s important to use SMA responsibly and ethically. As marketers, we must be mindful of how our actions affect our customers and their trust in us. With great power comes great responsibility – and SMA is no exception. The data generated by social networks can be used for good or ill, depending on how it’s handled. For example, some companies may use SMA to gather data about their customers without properly informing them or obtaining their consent. This not only violates privacy laws but also erodes public trust in businesses and brands. On the other hand, companies that employ SMA responsibly can gain valuable insights that can help them better understand their target audience and tailor their strategies accordingly. The key is to ensure that your company’s approach to using SMA is ethical and transparent. That means taking steps such as establishing clear policies regarding data collection and usage, educating employees on best practices, and providing customers with options to opt-out or limit the amount of data they share with you. When used correctly, social media analytics has the potential to revolutionize marketing – but only if we make sure we do so responsibly and ethically. Let’s make way for the future of SMM by embracing the power of social media analytics – but doing so in a way that respects our customers’ rights and privacy!

Make Way for the Future of SMM: Unleash the Power of Social Media Analytics

Social media analytics is quickly becoming one of the most powerful tools in a business’s arsenal. With its ability to measure, track, and analyze data from social media platforms, it provides insights that can help businesses make smarter decisions and increase their bottom line. But what are some of the concrete benefits that businesses can experience when they utilize social media analytics? First and foremost, social media analytics can provide invaluable insights into customer behavior and preferences. By tracking customer engagement on various platforms, businesses can gain insights into what types of content are resonating with their audiences and what kind of messaging is most effective in driving sales or achieving other desired outcomes. This kind of data can be used to refine a company’s marketing strategy as well as inform product development decisions. Social media analytics also gives companies access to real-time data about their competitors’ activities. By tracking their competitors’ campaigns, businesses can gain valuable insights into their strategies and how they’re reaching their target audiences. This information can then be used to inform a company’s own marketing efforts and give them an edge over their competitors. Finally, social media analytics provides businesses with valuable data about how their campaigns are performing in comparison to industry standards. Companies can use this data to benchmark their performance against others in their industry, giving them a better understanding of where they stand in terms of reach and engagement levels as well as providing them with an opportunity to refine their strategies accordingly. In short, social media analytics has become an essential tool for any business looking to maximize its potential on social media platforms. With its ability to provide valuable insights into customer behavior, keep tabs on competitors’ activities, and benchmark performance against industry standards, it has become one of the most powerful tools available for businesses seeking success on social media.

 Power of Social Media Analytics for a Brighter Future

The future of social media marketing is an exciting one. With the right tools, data, and insights, companies can leverage powerful analytics to make informed decisions and maximize their ROI. But with great power comes great responsibility. It's up to us to ensure that we are using this data ethically and responsibly in order to create a brighter future for ourselves and our customers. It's time to think outside the box and embrace the power of social media analytics. Let’s unlock its potential by embracing the possibilities it offers and unlocking new opportunities for growth. By harnessing the power of social media analytics, we can make way for a brighter future!




Being-Your-Own-Boss” Business Opportunity

Being-Your-Own-Boss Business Opportunity


An Inspirational Guide to Becoming Your Own Boss

Are you tired of the daily grind of the 9-5 lifestyle? Are you looking for a more flexible and creative way to make money? If so, becoming your own boss might be the perfect solution for you. This inspirational guide will provide you with an introduction to the many benefits of being your own boss.


When you become your own boss, you can create a career that fits perfectly into your lifestyle. You can choose when and how much work you want to do, and when it's time to take a break. You can also determine which projects interest you, allowing you to explore new opportunities and develop new skills.


Being your own boss also gives you the freedom to set your own rates and prices. You can decide how much money you want to make and how much value you bring to clients. This means that not only do you have control over your income, but also over the quality of work that goes out into the world.


Finally, becoming your own boss allows for creativity and experimentation. When working for yourself, there's no one telling you what is or isn't possible. You have complete freedom to try new ideas and take risks without fear of failure or judgment.


These are just some of the many benefits of becoming your own boss. With this inspirational guide as a starting point, why not start exploring what it would be like to be in control of your career?


An Inspirational Guide to Becoming Your Own Boss: Steps for Creating a Business Plan and Setting Goals

Are you ready to take the leap and become your own boss? Starting your own business requires ambition, determination, and an unwavering commitment to achieving success. Before you take the plunge, it’s important to have a plan in place that will guide you through the process of becoming a successful entrepreneur. The first step is to create a business plan. This document should outline all of your goals and objectives, as well as provide an overview of how you plan to achieve them. When designing your business plan, be sure to include:

A description of the product or service that you’re offering.

A target market analysis.

Projected financial statements.

A risk assessment.

Once your business plan is complete, it’s time to set some goals for yourself. Ask yourself what success looks like for your business and then set reasonable goals that will help you get there. Don’t forget to break down those big goals into smaller milestones so that you can easily track your progress along the way. Finally, make sure that each goal has a timeline associated with it so that you have something tangible to strive for. Creating a business plan and setting goals are essential steps when starting any new venture. By taking the time to properly prepare for success, you’ll be able to focus on what matters most – growing your business! Good luck!

Finding Your Niche and Identifying Your Target Market

Are you considering taking the plunge and becoming your own boss? Congratulations! This is an incredibly exciting journey that can open up a world of opportunity. Before you can start your own business, however, it’s essential to identify your niche and target market. When you’re starting out, it can be tempting to try and appeal to everyone. However, this is rarely the best approach. You need to think about who you’re trying to target with your product or service. What kind of customer do you want to attract? What makes them different from other customers? Once you have a better idea of your target customer, it’s time to define your niche. Think about what makes your business unique compared to competitors in the same industry. What value do you bring that others don’t? How can you stand out from the crowd? It can also help to examine the current trends in your industry and see how they fit into your business plan. Are there any new trends that could benefit your business? If so, how can you use them to create a competitive advantage for yourself? Identifying your niche and target market is essential for any successful business. It will help guide every decision you make moving forward, from marketing strategies to product development. With clarity on who you’re targeting and why they should choose you over other options, it will be easier for you to focus on growth and success!

Determining Start-Up Costs and Funding Options

Starting your own business can be an exciting yet daunting task. Knowing how much money you need to get started is a great first step in becoming your own boss. Before you take the plunge, it's important to understand the start-up costs associated with launching a business. You'll need to consider expenses such as equipment, materials, office space, legal fees, taxes, and insurance. Additionally, you'll need to have enough money saved up for the first few months of operation to cover any unexpected costs that may arise. Once you have a better idea of how much money you will need to get started on your venture, it's time to look into funding options. Depending on the type of business you are starting, there are many potential sources of capital available such as angel investors, venture capitalists, grants from local organizations or government programs, or even crowdfunding platforms. It's essential that you do your research and be aware of all the options available so that you can make an informed decision about which route is best for your business. Finally, don't forget about bootstrapping! Bootstrapping means finding ways to fund your venture without relying on outside sources of capital such as using personal savings or selling items that are no longer necessary. This can be an excellent way to put together a viable start-up without having to rely on outside investors or loans. No matter what route you decide to take when funding your business venture, understanding start-up costs and exploring different funding options is an essential part of becoming your own boss! With some creativity and research skills in hand, you can be well on your way towards achieving success in creating your dream business!

motivates them? Knowing this information will help you create marketing messages tailored to their needs. Second, experiment with different types of content. Content marketing is a great way to drive traffic to your website or promote special offers. Try creating Blog posts, podcasts, videos, infographics and other types of content that will engage your audience. Third, use social media strategically. Social media can be a powerful tool for connecting with customers and building relationships with potential customers. Post regularly and engage with followers by responding to comments and messages promptly. Fourth, don’t forget about traditional methods like print advertising or direct mail campaigns. Even in the digital age, print advertising can still be effective in reaching certain audiences or promoting special offers or events. Finally, track the results from each campaign so that you can adjust accordingly in the future. This will help you identify which strategies are working best for you so that you can focus on those going forward. Becoming your own boss is an exciting adventure! With these tips in mind, you’ll be well on your way to developing successful marketing and promotional strategies for your business venture!

Tech  Dot-Com start-Ups  Sample and Example

AviaTech : Aviation + Technology

www.Air-Aviator.com

AgroTech 

BlogTech : Blog + Technology

www.AlfaBloggers.com

BioTech: Biology + Technology

CabTech: Cab + Technology

www.AllIndiaCarTaxiClub.com 

CleanTech: Clean + Technology

DevTech: Development + Technology

DirTech : Directory + Technology  

www.10BestInCity.com 

EdTech: Education + Technology 

www.BestInternationalEducation.com

FinTech: Finance + Technology  

www.Fintech-Start-Up.com

FoodTech: Food + Technology

FemTech: Female + Technology  

www.Portrait-Business-Woman.com

GuideTech 

www.GuideByLocal.com

GreenTech: Green + Technology 

www.SatpuraJungleRetreat.com

HealthTech: Health + Technology 

www.AnxietyAttak.com

InfoTech 

www.WorldOfAirplane.com

InsurTech: Insurance + Technology

JobTech 

www.Flying-Crews.com

KidsTech 

LegalTech: Legal + Technology

MediTech: Medical + Technology

NetTech 

OpsTech 

www.AirCrewsAviation.com

PropTech: Property + Technology

RealTech 

RetailTech: Retail + Technology

www.AllInOneShoppingApps.com

RegTech: Regulation + Technology

SoftTech 

TravelTech 

WealthTech: Wealth + Technology

#B2B,  #Businesses, #Money,  #Table, #branding #personalbranding #content marketing #growth #leads #marketing #create 




www.10BestInCity.com

www.AirCrewsAviation.com

www.Air-Aviator.com

www.AlfaBloggers.com

www.AllIndiaCarTaxiClub.com

www.AllInOneShoppingApps.com

www.Flying-Crews.com

www.Portrait-Business-Woman.com

www.BestInternationalEducation.com

www.SatpuraJungleRetreat.com

www.WorldOfAirplane.com

www.Fintech-Start-Up.com

www.AnxietyAttak.com

www.GuideByLocal.com

https://linktr.ee/AirAviator

https://linktr.ee/10bestincity

https://linktr.ee/LessonfromBusinessLeader

https://linktr.ee/w2win


Text Mining: Techniques for analyzing unstructured text data

Text Mining: Techniques for analyzing unstructured text data

 


The practise of drawing insightful conclusions and usable information from unstructured or semi-structured text data is called text mining, often referred to as text analytics. Text information can be found in a wide range of places, including emails, social media posts, evaluations of products and services, news stories, and more.

Natural language processing (NLP) techniques are used in text mining to analyse text data and uncover insightful patterns and relationships. Sentiment analysis, topic modelling, named entity recognition, and text categorization are a few popular text mining approaches.

Numerous sectors and applications, including market research, customer support, social media monitoring, fraud detection, and more, use text mining. Organisations can learn critical information about customer preferences, market trends, and other important aspects that can guide business decisions and strategies by analysing enormous volumes of text data.Numerous sectors and applications, including market research, customer support, social media monitoring, fraud detection, and more, use text mining. Organisations can learn critical information about customer preferences, market trends, and other important aspects that can guide business decisions and strategies by analysing enormous volumes of text data.


What exactly is unstructured text data? 


Text data that doesn't adhere to a particular format or organisation is referred to as unstructured text data. Unstructured text data lacks a set framework or schema, making it more difficult to analyse and comprehend than structured data, which is organised and simple to search (such as data in a database or spreadsheet).


Emails, social media posts, customer reviews, product comments, news stories, and other text-based content are examples of unstructured text data. Because it may contain grammatical mistakes, slang or colloquial language, and other subtleties that may be challenging for computer systems to interpret, this type of data can be challenging to process and analyse.


Regardless of these difficulties, unstructured text data offers insightful information that businesses can use to enhance their offerings to clients. Organisations can utilise data-driven decision-making and natural language processing to extract valuable patterns and insights from unstructured text data, giving them a competitive edge.



Unstructured text data can be analysed using a variety of methods. Among the most popular methods are:


Text Preprocessing: This method entails preparing the text data for analysis by cleaning it. Among the tasks involved in text preparation are the elimination of stop words, stemming, lemmatization, and changing the text's case to lowercase.


Sentiment Analysis: This method involves identifying the sentiment, such as whether it is favourable, negative, or neutral, reflected in the text data. Sentiment analysis is frequently used to examine reviews of products and customer feedback.


Topic Modeling: Using this method, you may find themes or subjects in the text data. To analyse big sets of documents, such academic papers or news items, topic modelling is frequently utilised.


Named Entity Recognition: This method entails locating and extracting identified entities from the text data, including individuals, groups, and places. Search engines and information extraction frequently employ named entity recognition.


Text Classification: Using this method, text data is categorised according to its content into specified categories. Spam filtering, language identification, and content categorization all frequently use text classification.


Text Summarization: Using this technique, the most crucial information is extracted from lengthy texts or text data. Research papers, court filings, and news items frequently use text summarising.


Entity Sentiment Analysis: This method entails determining the attitude towards particular entities mentioned in the text data. Customer feedback analysis and social media monitoring both frequently employ entity sentiment analysis.


There are numerous methods used to analyse unstructured text data; here are just a few examples. By utilising these tactics, businesses can learn essential information about market trends, client preferences, and other crucial elements that can guide strategic business decisions.


๐Ÿ‘Anushree Shinde e[ MBA] 

Business Analyst

10BestInCity.com Venture

anushree@10bestincity.com

10bestincityanushree@gmail.com

www.10BestInCity.com 

https://www.portrait-business-woman.com/2023/05/anushree-shinde.html



#TextMining, #NaturalLanguageProcessing, 

#SentimentAnalysis, #TopicModeling, #TextClassification, #TextAnalytics, #MachineLearning, #DataMining, #BigData

#InformationRetrieval, #TextPreprocessing, 

#NamedEntityRecognition, #WordEmbedding

#CorpusAnalysis, #FeatureExtraction.

Follow the 5R Strategy at Home: REFUSE -> REDUCE -> REUSE -> REPAIR -> RECYCLE

Follow the 5R Strategy at Home:

REFUSE -> REDUCE -> REUSE -> REPAIR -> RECYCLE.




The World Generates 2.00Billion Tonnes of Municipal Solid Waste Annually

เคฆुเคจिเคฏा เคฎें เคนเคฐ เคธाเคฒ 2.00 เค…เคฐเคฌ เคŸเคจ เคจเค—เคฐเคชाเคฒिเค•ा เค ोเคธ เค•เคšเคฐा เคชैเคฆा เคนोเคคा เคนै।

Every year 2.00 billion tonnes of municipal solid waste is generated in the world.


OECD - Below are the top polluters in the OECD:


Average Dane = 850.6 kg/yr

Average American = 810.9 kg/year

Luxembourg average = 795.2 kg/year

Average Kiwi = 781.1 kg/year

Average Icelander = 735.1 kg/year


44% of waste is food

17% is paper

12% is plastic

5% is glass

4% is metal

2% is rubber and leather

2% is wood

14% is other ingredients


36.6% ended up in landfills

33% ended up in open dumps

And only 13.5% was recycled!


Most waste is not recycled with consequences for people, the planet and the profits! To stop this we have to go circular. Reduce waste, limit consumption and close the loop.


Follow the 5R strategy at home:


Refuse -> Reduce -> Reuse -> Repair -> Recycle.














เคฆुเคจिเคฏा เคฎें เคนเคฐ เคธाเคฒ 2.00 เค…เคฐเคฌ เคŸเคจ เคจเค—เคฐเคชाเคฒिเค•ा เค ोเคธ เค•เคšเคฐा เคชैเคฆा เคนोเคคा เคนै।


OECD - OCDE เคฎें เคถीเคฐ्เคท เคช्เคฐเคฆूเคทเค• เคจीเคšे เคฆिเค เค—เค เคนैं:


เค”เคธเคค เคกेเคจ = 850.6 เค•िเค—्เคฐा/เคตเคฐ्เคท

เค”เคธเคค เค…เคฎेเคฐिเค•ी = 810.9 เค•िเค—्เคฐा/เคตเคฐ्เคท

เคฒเค•्เคธเคฎเคฌเคฐ्เค— เค•ा เค”เคธเคค = 795.2 เค•िเค—्เคฐा/เคตเคฐ्เคท

เค”เคธเคค เค•ीเคตी = 781.1 เค•िเค—्เคฐा/เคตเคฐ्เคท

เค”เคธเคค เค†เค‡เคธเคฒैंเคกเคฐ = 735.1 เค•िเค—्เคฐा / เคตเคฐ्เคท


44% เค•เคšเคฐा เคญोเคœเคจ เคนै

17% เค•ाเค—เคœ เคนै

12% เคช्เคฒाเคธ्เคŸिเค• เคนै

5% เค•ांเคš เคนै

4% เคงाเคคु เคนै

2% เคฐเคฌเคฐ เค”เคฐ เคšเคฎเคก़ा เคนै

2% เคฒเค•เคก़ी เคนै

14% เค…เคจ्เคฏ เคธाเคฎเค—्เคฐी เคนै

36.6% เคฒैंเคกเคซिเคฒ เคฎें เคธเคฎाเคช्เคค เคนो เค—เคฏा

33% เค–ुเคฒे เคกंเคช เคฎें เคธเคฎाเคช्เคค เคนो เค—เคฏा

เค”เคฐ เค•ेเคตเคฒ 13.5% เคชुเคจเคฐ्เคจเคตीเคจीเค•เคฐเคฃ เค•िเคฏा เค—เคฏा เคฅा!


เค…เคงिเค•ांเคถ เค•เคšเคฐे เค•ो เคฒोเค—ों, เค—्เคฐเคน เค”เคฐ เคฒाเคญ เค•े เคชเคฐिเคฃाเคฎों เค•े เคธाเคฅ เคชुเคจเคฐ्เคจเคตीเคจीเค•เคฐเคฃ เคจเคนीं เค•िเคฏा เคœाเคคा เคนै! เค‡เคธे เคฐोเค•เคจे เค•े เคฒिเค เคนเคฎें เคธเคฐ्เค•ुเคฒเคฐ เคœाเคจा เคนोเค—ा। เค•เคšเคฐे เค•ो เค•เคฎ เค•เคฐें, เค–เคชเคค เค•ो เคธीเคฎिเคค เค•เคฐें เค”เคฐ เคฒूเคช เค•ो เคฌंเคฆ เค•เคฐें।


เค˜เคฐ เคชเคฐ 5R เคฐเคฃเคจीเคคि เค•ा เคชाเคฒเคจ เค•เคฐें:


เคฎเคจा เค•เคฐें -> เค•เคฎ เค•เคฐें -> เคชुเคจ: เค‰เคชเคฏोเค— เค•เคฐें -> เคฎเคฐเคฎ्เคฎเคค เค•เคฐें -> เคชुเคจเคฐ्เคšเค•्เคฐ เค•เคฐें।


 

The top polluters in OECD - OCDE are as below:


Average Dane = 850.6 Kg / year

Average American = 810.9 Kg / year

Average Luxembourger = 795.2 Kg / year

Average Kiwi = 781.1 Kg / year

Average Icelander = 735.1 Kg / year


44% of the waste is Food

17% is paper

12% is Plastic

5% is glass

4% is metal

2% is rubber and leather

2% is wood

14% is other material


36.6% ended up in landfills

33% ended up in open dumps

And only 13.5% was recycled!


Majority of the waste is not recycled with consequences for people, planet, and profit! To stop this, we need to go circular. Minimize waste, limit consumption & close the loop.

Follow the 5R strategy at home:

REFUSE -> REDUCE -> REUSE -> REPAIR -> RECYCLE.


Anxiety, Depression, Fear, Frustration, Guilt & Hopelessness Is The New Normal Post Covid19

Anxiety, Depression, Fear, Frustration and Guilt is New Normal Post Covid

เคšिंเคคा, เค…เคตเคธाเคฆ, เคญเคฏ, เคจिเคฐाเคถा เค”เคฐ เค…เคชเคฐाเคง เคฌोเคง เคจ्เคฏू เคจॉเคฐ्เคฎเคฒ เคชोเคธ्เคŸ เค•ोเคตिเคฆ เคนै



Anxiety, Depression, Fear, Frustration, Guilt & Hopelessness  


Is The New Normal Post Covid19

The world is facing unprecedented times with the outbreak of COVID-19. The pandemic has significantly changed the way people live, work and interact with each other. It has also affected mental health in ways never expected. The pandemic has given rise to a range of emotions such asAnxiety, Depression, Fear, Frustration, Guilt & Hopelessness   which have become the new normal for many.


Anxiety

Anxiety is a feeling of uneasiness and worry that is often accompanied by physical symptoms such as a racing heart, sweating, and trembling. Anxiety can be triggered by a number of factors, including fear of getting infected, financial instability, and job loss. There has been an increase in the number of people experiencing anxiety due to the pandemic. Anxiety can manifest in different ways for different people. Some may experience intense fear and panic attacks, while others may feel constant restlessness. Coping with anxiety can be challenging, and it's important to seek help if you're struggling with it.


Depression

Depression is a mental health disorder that affects millions of people worldwide. It is characterized by feelings of sadness, hopelessness, and loss of interest in activities that were once enjoyable. The pandemic has led to an increase in the number of people experiencing depression. Depression can be caused by many factors, including genetic predisposition, environmental factors, and life events. The pandemic has led to many life events that can trigger depression, such as job loss and social isolation. Coping with depression can be challenging, and it's important to seek help if you're struggling with it.


Fear of Failure

There has been an increase in the number of people experiencing fear due to the pandemic. Fear can be triggered by many factors, such as fear of getting infected, fear of losing a loved one, and fear of financial instability. Fear can manifest in different ways for different people. Some may experience intense fear and panic attacks, while others may feel constant restlessness. Coping with fear can be challenging, and it's important to seek help if you're struggling with it. There are many strategies that can help reduce fear, such as deep breathing exercises, mindfulness, and talking with a therapist.


Frustration  Or Disappointment

The pandemic has led to an increase in the number of people experiencing depression. Depression can be triggered by a number of factors, such as an inability to do things that were once enjoyable, a lack of control over the situation, and an inability to plan for the future. Coping with depression can be challenging, and it's important to get help if you're struggling with it. There are many strategies that can help reduce frustration, such as practicing gratitude, staying connected with loved ones, and engaging in enjoyable activities.


Guilt 

The pandemic has increased the number of people experiencing guilt. Guilt can be triggered by many factors, such as the inability to provide for one's family, the inability to help those in need, and the feeling of not doing enough. Coping with guilt can be challenging, and it's important to seek help if you're struggling with it. There are many strategies that can help reduce guilt, such as practicing self-compassion, volunteering, and focusing on the things you can control.


Depression in  Creators and Youth

The pandemic has had a significant impact on the mental health of young people. Depression is one of the most common mental health disorders among youth. The pandemic has led to an increase in the number of young people experiencing depression. Depression in youth can be caused by a number of factors, such as disruption of routine and social isolation. Dealing with depression in youth can be challenging, and it's important to get help if you're struggling with it. There are many strategies that can help reduce depression in youth, such as staying connected with peers, engaging in enjoyable activities, and seeking professional help.


Disappointment among  Creators and Youth

There has also been an increase in the number of young people experiencing depression due to the pandemic. Depression in youth can be caused by a number of factors, such as an inability to see friends and engage in extracurricular activities.

Dealing with depression in youth can be challenging, and it's important to seek help if you're struggling with it. There are many strategies that can help reduce depression in youth, such as staying connected with peers, engaging in enjoyable activities, and seeking professional help.


Guilt in Creators and Youth

The pandemic has also led to an increase in the number of young people experiencing guilt. Guilt in youth can be caused by a range of factors, such as the feeling of not doing enough to help those in need. Coping with guilt in youth can be challenging, and it is important to seek help if you are struggling with it. There are a range of strategies that can help alleviate guilt in youth, such as practicing self-compassion, volunteering, and focusing on the things that they can control. 

The Pandemic has led to a range of emotions that have become the new normal for many people. It is important to seek help if you are struggling with any of these emotions. There are a range of strategies that can help alleviate these emotions, and it is important to find the ones that work best for you. Remember that it is okay to not be okay, and seeking help is a sign of strength. 

Call to Action: 

If you or someone you know is struggling with their mental health, please seek help. There are resources available that can help you navigate these challenging times.

Improve Team Collaboration with shared candidate profiles, notes, and touch point history that help teammates align on crucial hiring decisions.

Reason for Less Productivity in Creators and Youth 

Anxiety in Youth, 

Depression in Youth,, 

Fear of Failure, 

Frustration in Youth, 

Guilt in Youth,

Hopelessness,

Covid19,

Best  Tips For Effective Networking for Creators and Youth 


Anxiety, Depression, Fear, Frustration, Guilt & Hopelessness  Is The New Normal Post Covid19

เคšिंเคคा, เค…เคตเคธाเคฆ, เคญเคฏ, เคจिเคฐाเคถा เค”เคฐ เค…เคชเคฐाเคง เคฌोเคง เคจ्เคฏू เคจॉเคฐ्เคฎเคฒ เคชोเคธ्เคŸ เค•ोเคตिเคฆ เคนै

เคฆुเคจिเคฏा เค•ोเคตिเคก-19 เค•े เคช्เคฐเค•ोเคช เค•े เคธाเคฅ เค…เคญूเคคเคชूเคฐ्เคต เคธเคฎเคฏ เค•ा เคธाเคฎเคจा เค•เคฐ เคฐเคนी เคนै। เคฎเคนाเคฎाเคฐी เคจे เคฒोเค—ों เค•े เคฐเคนเคจे, เค•ाเคฎ เค•เคฐเคจे เค”เคฐ เคเค• เคฆूเคธเคฐे เค•े เคธाเคฅ เคฌाเคคเคšीเคค เค•เคฐเคจे เค•े เคคเคฐीเค•े เคฎें เคฎเคนเคค्เคตเคชूเคฐ्เคฃ เคฌเคฆเคฒाเคต เค•िเคฏा เคนै। เค‡เคธเคจे เคฎाเคจเคธिเค• เคธ्เคตाเคธ्เคฅ्เคฏ เค•ो เค‰เคจ เคคเคฐीเค•ों เคธे เคญी เคช्เคฐเคญाเคตिเคค เค•िเคฏा เคนै เคœिเคธเค•ी เค•เคญी เค‰เคฎ्เคฎीเคฆ เคจเคนीं เค•ी เค—เคˆ เคฅी। เคฎเคนाเคฎाเคฐी เคจे เคšिंเคคा, เค…เคตเคธाเคฆ, เคญเคฏ, เคนเคคाเคถा เค”เคฐ เค…เคชเคฐाเคงเคฌोเคง เคœैเคธी เค•เคˆ เคญाเคตเคจाเค“ं เค•ो เคœเคจ्เคฎ เคฆिเคฏा เคนै, เคœो เค•เคˆ เคฒोเค—ों เค•े เคฒिเค เคจเคฏा เคธाเคฎाเคจ्เคฏ เคนो เค—เคฏा เคนै।


เคšिंเคคा

เคšिंเคคा เคฌेเคšैเคจी เค”เคฐ เคšिंเคคा เค•ी เคญाเคตเคจा เคนै เคœो เค…เค•्เคธเคฐ เคถाเคฐीเคฐिเค• เคฒเค•्เคทเคฃों เค•े เคธाเคฅ เคนोเคคी เคนै เคœैเคธे เค•ि เคฆिเคฒ เค•ा เคฆौเคก़เคจा, เคชเคธीเคจा เค†เคจा เค”เคฐ เค•ांเคชเคจा। เคšिंเคคा เค•เคˆ เค•ाเคฐเค•ों เคธे เคถुเคฐू เคนो เคธเค•เคคी เคนै, เคœिเคธเคฎें เคธंเค•्เคฐเคฎिเคค เคนोเคจे เค•ा เคกเคฐ, เคตिเคค्เคคीเคฏ เค…เคธ्เคฅिเคฐเคคा เค”เคฐ เคจौเค•เคฐी เค›ूเคŸเคจा เคถाเคฎिเคฒ เคนै। เคฎเคนाเคฎाเคฐी เค•े เค•ाเคฐเคฃ เคšिंเคคा เค•ा เค…เคจुเคญเคต เค•เคฐเคจे เคตाเคฒे เคฒोเค—ों เค•ी เคธंเค–्เคฏा เคฎें เคตृเคฆ्เคงि เคนुเคˆ เคนै। เคšिंเคคा เค…เคฒเค—-เค…เคฒเค— เคฒोเค—ों เค•े เคฒिเค เค…เคฒเค—-เค…เคฒเค— เคคเคฐीเค•ों เคธे เคช्เคฐเค•เคŸ เคนो เคธเค•เคคी เคนै। เค•ुเค› เค•ो เคคीเคต्เคฐ เคญเคฏ เค”เคฐ เค˜เคฌเคฐाเคนเคŸ เค•े เคฆौเคฐे เค•ा เค…เคจुเคญเคต เคนो เคธเค•เคคा เคนै, เคœเคฌเค•ि เค…เคจ्เคฏ เค•ो เคฒเค—ाเคคाเคฐ เคฌेเคšैเคจी เคฎเคนเคธूเคธ เคนो เคธเค•เคคी เคนै। เคšिंเคคा เคธे เคฎुเค•ाเคฌเคฒा เค•เคฐเคจा เคšुเคจौเคคीเคชूเคฐ्เคฃ เคนो เคธเค•เคคा เคนै, เค”เคฐ เค…เค—เคฐ เค†เคช เค‡เคธเคธे เคœूเค เคฐเคนे เคนैं เคคो เคฎเคฆเคฆ เคฒेเคจा เคฎเคนเคค्เคตเคชूเคฐ्เคฃ เคนै।


เค…เคตเคธाเคฆ

เคกिเคช्เคฐेเคถเคจ เคเค• เคฎाเคจเคธिเค• เคธ्เคตाเคธ्เคฅ्เคฏ เคตिเค•ाเคฐ เคนै เคœो เคฆुเคจिเคฏा เคญเคฐ เคฎें เคฒाเค–ों เคฒोเค—ों เค•ो เคช्เคฐเคญाเคตिเคค เค•เคฐเคคा เคนै। เคฏเคน เค‰เคฆाเคธी, เคจिเคฐाเคถा เค”เคฐ เค‰เคจ เค—เคคिเคตिเคงिเคฏों เคฎें เคฐुเคšि เค•ी เค•เคฎी เค•ी เคญाเคตเคจाเค“ं เค•ी เคตिเคถेเคทเคคा เคนै เคœो เค•เคญी เคธुเค–เคฆ เคฅीं। เคฎเคนाเคฎाเคฐी เค•े เค•ाเคฐเคฃ เค…เคตเคธाเคฆ เค•ा เค…เคจुเคญเคต เค•เคฐเคจे เคตाเคฒे เคฒोเค—ों เค•ी เคธंเค–्เคฏा เคฎें เคตृเคฆ्เคงि เคนुเคˆ เคนै। เค…เคตเคธाเคฆ เค•เคˆ เค•ाเคฐเค•ों เค•े เค•ाเคฐเคฃ เคนो เคธเค•เคคा เคนै, เคœिเคจเคฎें เค†เคจुเคตंเคถिเค• เคช्เคฐเคตृเคค्เคคि, เคชเคฐ्เคฏाเคตเคฐเคฃीเคฏ เค•ाเคฐเค• เค”เคฐ เคœीเคตเคจ เค•ी เค˜เคŸเคจाเคं เคถाเคฎिเคฒ เคนैं। เคฎเคนाเคฎाเคฐी เคจे เคœीเคตเคจ เค•ी เค•เคˆ เค˜เคŸเคจाเค“ं เค•ो เคœเคจ्เคฎ เคฆिเคฏा เคนै เคœो เค…เคตเคธाเคฆ เค•ो เคŸ्เคฐिเค—เคฐ เค•เคฐ เคธเค•เคคी เคนैं, เคœैเคธे เค•ि เคจौเค•เคฐी เค›ूเคŸเคจा เค”เคฐ เคธाเคฎाเคœिเค• เค…เคฒเค—ाเคต। เค…เคตเคธाเคฆ เคธे เคฎुเค•ाเคฌเคฒा เค•เคฐเคจा เคšुเคจौเคคीเคชूเคฐ्เคฃ เคนो เคธเค•เคคा เคนै, เค”เคฐ เคฏเคฆि เค†เคช เค‡เคธเคธे เคœूเค เคฐเคนे เคนैं เคคो เคฎเคฆเคฆ เคฒेเคจा เคฎเคนเคค्เคตเคชूเคฐ्เคฃ เคนै।


เคกเคฐ

เคฎเคนाเคฎाเคฐी เค•े เค•ाเคฐเคฃ เคกเคฐ เค•ा เค…เคจुเคญเคต เค•เคฐเคจे เคตाเคฒे เคฒोเค—ों เค•ी เคธंเค–्เคฏा เคฎें เคตृเคฆ्เคงि เคนुเคˆ เคนै। เคกเคฐ เค•เคˆ เค•ाเคฐเค•ों เคธे เคถुเคฐू เคนो เคธเค•เคคा เคนै, เคœैเคธे เค•ि เคธंเค•्เคฐเคฎिเคค เคนोเคจे เค•ा เคกเคฐ, เค•िเคธी เคช्เคฐिเคฏเคœเคจ เค•ो เค–ोเคจे เค•ा เคกเคฐ เค”เคฐ เคตिเคค्เคคीเคฏ เค…เคธ्เคฅिเคฐเคคा เค•ा เคกเคฐ। เคกเคฐ เค…เคฒเค—-เค…เคฒเค— เคฒोเค—ों เค•े เคฒिเค เค…เคฒเค—-เค…เคฒเค— เคคเคฐीเค•ों เคธे เคช्เคฐเค•เคŸ เคนो เคธเค•เคคा เคนै। เค•ुเค› เค•ो เคคीเคต्เคฐ เคญเคฏ เค”เคฐ เค˜เคฌเคฐाเคนเคŸ เค•े เคฆौเคฐे เค•ा เค…เคจुเคญเคต เคนो เคธเค•เคคा เคนै, เคœเคฌเค•ि เค…เคจ्เคฏ เค•ो เคฒเค—ाเคคाเคฐ เคฌेเคšैเคจी เคฎเคนเคธूเคธ เคนो เคธเค•เคคी เคนै। เคกเคฐ เคธे เคฎुเค•ाเคฌเคฒा เค•เคฐเคจा เคšुเคจौเคคीเคชूเคฐ्เคฃ เคนो เคธเค•เคคा เคนै, เค”เคฐ เค…เค—เคฐ เค†เคช เค‡เคธเคธे เคœूเค เคฐเคนे เคนैं เคคो เคฎเคฆเคฆ เคฒेเคจा เคฎเคนเคค्เคตเคชूเคฐ्เคฃ เคนै। เคเคธी เค•เคˆ เคฐเคฃเคจीเคคिเคฏाँ เคนैं เคœो เคกเคฐ เค•ो เค•เคฎ เค•เคฐเคจे เคฎें เคฎเคฆเคฆ เค•เคฐ เคธเค•เคคी เคนैं, เคœैเคธे เค•ि เค—เคนเคฐी เคธाँเคธ เคฒेเคจे เค•े เคต्เคฏाเคฏाเคฎ, เคฆिเคฎाเค—ीเคชเคจ เค”เคฐ เคšिเค•िเคค्เคธเค• เคธे เคฌाเคค เค•เคฐเคจा।


เคจिเคฐाเคถा

เคฎเคนाเคฎाเคฐी เค•े เค•ाเคฐเคฃ เคจिเคฐाเคถा เค•ा เค…เคจुเคญเคต เค•เคฐเคจे เคตाเคฒे เคฒोเค—ों เค•ी เคธंเค–्เคฏा เคฎें เคตृเคฆ्เคงि เคนुเคˆ เคนै। เคจिเคฐाเคถा เค•เคˆ เค•ाเคฐเค•ों เคธे เคถुเคฐू เคนो เคธเค•เคคी เคนै, เคœैเคธे เค•ि เค‰เคจ เคšीเคœों เค•ो เค•เคฐเคจे เคฎें เค…เคธเคฎเคฐ्เคฅเคคा เคœो เคเค• เคฌाเคฐ เค†เคจंเคฆเคฆाเคฏเค• เคฅीं, เคธ्เคฅिเคคि เคชเคฐ เคจिเคฏंเคค्เคฐเคฃ เค•ी เค•เคฎी เค”เคฐ เคญเคตिเคท्เคฏ เค•े เคฒिเค เคฏोเคœเคจा เคฌเคจाเคจे เคฎें เค…เคธเคฎเคฐ्เคฅเคคा। เคนเคคाเคถा เคธे เคฎुเค•ाเคฌเคฒा เค•เคฐเคจा เคšुเคจौเคคीเคชूเคฐ्เคฃ เคนो เคธเค•เคคा เคนै, เค”เคฐ เคฏเคฆि เค†เคช เค‡เคธเคธे เคœूเค เคฐเคนे เคนैं เคคो เคธเคนाเคฏเคคा เคช्เคฐाเคช्เคค เค•เคฐเคจा เคฎเคนเคค्เคตเคชूเคฐ्เคฃ เคนै। เคเคธी เค•เคˆ เคฐเคฃเคจीเคคिเคฏाँ เคนैं เคœो เคนเคคाเคถा เค•ो เค•เคฎ เค•เคฐเคจे เคฎें เคฎเคฆเคฆ เค•เคฐ เคธเค•เคคी เคนैं, เคœैเคธे เค•ि เค•ृเคคเคœ्เคžเคคा เค•ा เค…เคญ्เคฏाเคธ เค•เคฐเคจा, เคช्เคฐिเคฏเคœเคจों เค•े เคธाเคฅ เคœुเคก़े เคฐเคนเคจा เค”เคฐ เค†เคจंเคฆเคฆाเคฏเค• เค—เคคिเคตिเคงिเคฏों เคฎें เคถाเคฎिเคฒ เคนोเคจा।


เค…เคชเคฐाเคง

เคฎเคนाเคฎाเคฐी เค•े เค•ाเคฐเคฃ เค…เคชเคฐाเคงเคฌोเคง เค•ा เค…เคจुเคญเคต เค•เคฐเคจे เคตाเคฒे เคฒोเค—ों เค•ी เคธंเค–्เคฏा เคฎें เคตृเคฆ्เคงि เคนुเคˆ เคนै। เค…เคชเคฐाเคง เคฌोเคง เค•เคˆ เค•ाเคฐเค•ों เคธे เคถुเคฐू เคนो เคธเค•เคคा เคนै, เคœैเคธे เค•िเคธी เค•े เคชเคฐिเคตाเคฐ เค•े เคฒिเค เคช्เคฐเคฆाเคจ เค•เคฐเคจे เคฎें เค…เคธเคฎเคฐ्เคฅเคคा, เคœเคฐूเคฐเคคเคฎंเคฆ เคฒोเค—ों เค•ी เคฎเคฆเคฆ เค•เคฐเคจे เคฎें เค…เคธเคฎเคฐ्เคฅเคคा เค”เคฐ เคชเคฐ्เคฏाเคช्เคค เคจเคนीं เค•เคฐเคจे เค•ी เคญाเคตเคจा। เค…เคชเคฐाเคง เคฌोเคง เคธे เคฎुเค•ाเคฌเคฒा เค•เคฐเคจा เคšुเคจौเคคीเคชूเคฐ्เคฃ เคนो เคธเค•เคคा เคนै, เค”เคฐ เคฏเคฆि เค†เคช เค‡เคธเคธे เคœूเค เคฐเคนे เคนैं เคคो เคฎเคฆเคฆ เคฒेเคจा เคฎเคนเคค्เคตเคชूเคฐ्เคฃ เคนै। เคเคธी เค•เคˆ เคฐเคฃเคจीเคคिเคฏाँ เคนैं เคœो เค…เคชเคฐाเคงเคฌोเคง เค•ो เค•เคฎ เค•เคฐเคจे เคฎें เคฎเคฆเคฆ เค•เคฐ เคธเค•เคคी เคนैं, เคœैเคธे เค•ि เค†เคค्เคฎ-เค•เคฐुเคฃा เค•ा เค…เคญ्เคฏाเคธ เค•เคฐเคจा, เคธ्เคตेเคš्เค›ा เคธे เค•ाเคฎ เค•เคฐเคจा เค”เคฐ เค‰เคจ เคšीเคœ़ों เคชเคฐ เคง्เคฏाเคจ เค•ेंเคฆ्เคฐिเคค เค•เคฐเคจा เคœिเคจ्เคนें เค†เคช เคจिเคฏंเคค्เคฐिเคค เค•เคฐ เคธเค•เคคे เคนैं।


เคฐเคšเคจाเค•ाเคฐों เค”เคฐ เคฏुเคตाเค“ं เคฎें เค…เคตเคธाเคฆ

เคฎเคนाเคฎाเคฐी เค•ा เคฏुเคตा เคฒोเค—ों เค•े เคฎाเคจเคธिเค• เคธ्เคตाเคธ्เคฅ्เคฏ เคชเคฐ เคฎเคนเคค्เคตเคชूเคฐ्เคฃ เคช्เคฐเคญाเคต เคชเคก़ा เคนै। เคกिเคช्เคฐेเคถเคจ เคฏुเคตाเค“ं เคฎें เคธเคฌเคธे เค†เคฎ เคฎाเคจเคธिเค• เคธ्เคตाเคธ्เคฅ्เคฏ เคตिเค•ाเคฐों เคฎें เคธे เคเค• เคนै। เคฎเคนाเคฎाเคฐी เค•े เค•ाเคฐเคฃ เค…เคตเคธाเคฆ เค•ा เค…เคจुเคญเคต เค•เคฐเคจे เคตाเคฒे เคฏुเคตाเค“ं เค•ी เคธंเค–्เคฏा เคฎें เคตृเคฆ्เคงि เคนुเคˆ เคนै। เคฏुเคตाเค“ं เคฎें เค…เคตเคธाเคฆ เค•เคˆ เค•ाเคฐเค•ों เค•े เค•ाเคฐเคฃ เคนो เคธเค•เคคा เคนै, เคœैเคธे เคฆिเคจเคšเคฐ्เคฏा เคฎें เคต्เคฏเคตเคงाเคจ เค”เคฐ เคธाเคฎाเคœिเค• เค…เคฒเค—ाเคต। เคฏुเคตाเคตเคธ्เคฅा เคฎें เค…เคตเคธाเคฆ เคธे เคจिเคชเคŸเคจा เคšुเคจौเคคीเคชूเคฐ्เคฃ เคนो เคธเค•เคคा เคนै, เค”เคฐ เคฏเคฆि เค†เคช เค‡เคธเคธे เคœूเค เคฐเคนे เคนैं เคคो เคธเคนाเคฏเคคा เคช्เคฐाเคช्เคค เค•เคฐเคจा เคฎเคนเคค्เคตเคชूเคฐ्เคฃ เคนै। เคเคธी เค•เคˆ เคฐเคฃเคจीเคคिเคฏाँ เคนैं เคœो เคฏुเคตाเค“ं เคฎें เค…เคตเคธाเคฆ เค•ो เค•เคฎ เค•เคฐเคจे เคฎें เคฎเคฆเคฆ เค•เคฐ เคธเค•เคคी เคนैं, เคœैเคธे เคธाเคฅिเคฏों เค•े เคธाเคฅ เคœुเคก़े เคฐเคนเคจा, เค†เคจंเคฆเคฆाเคฏเค• เค—เคคिเคตिเคงिเคฏों เคฎें เคถाเคฎिเคฒ เคนोเคจा เค”เคฐ เคชेเคถेเคตเคฐ เคฎเคฆเคฆ เคฒेเคจा।


เคฐเคšเคจाเค•ाเคฐों เค”เคฐ เคฏुเคตाเค“ं เคฎें เคจिเคฐाเคถा

เคฎเคนाเคฎाเคฐी เค•े เค•ाเคฐเคฃ เคจिเคฐाเคถा เค•ा เค…เคจुเคญเคต เค•เคฐเคจे เคตाเคฒे เคฏुเคตाเค“ं เค•ी เคธंเค–्เคฏा เคฎें เคญी เคตृเคฆ्เคงि เคนुเคˆ เคนै। เคฏुเคตाเค“ं เคฎें เคนเคคाเคถा เค•เคˆ เค•ाเคฐเค•ों เค•े เค•ाเคฐเคฃ เคนो เคธเค•เคคी เคนै, เคœैเคธे เคฆोเคธ्เคคों เค•ो เคฆेเค–เคจे เคฎें เค…เคธเคฎเคฐ्เคฅเคคा เค”เคฐ เคชाเค ्เคฏेเคคเคฐ เค—เคคिเคตिเคงिเคฏों เคฎें เคธंเคฒเค—्เคจ เคนोเคจा।

เคฏुเคตाเคตเคธ्เคฅा เคฎें เคนเคคाเคถा เคธे เคจिเคชเคŸเคจा เคšुเคจौเคคीเคชूเคฐ्เคฃ เคนो เคธเค•เคคा เคนै, เค”เคฐ เคฏเคฆि เค†เคช เค‡เคธเคธे เคœूเค เคฐเคนे เคนैं เคคो เคฎเคฆเคฆ เคฒेเคจा เคฎเคนเคค्เคตเคชूเคฐ्เคฃ เคนै। เคเคธी เค•เคˆ เคฐเคฃเคจीเคคिเคฏाँ เคนैं เคœो เคฏुเคตाเค“ं เคฎें เคนเคคाเคถा เค•ो เค•เคฎ เค•เคฐเคจे เคฎें เคฎเคฆเคฆ เค•เคฐ เคธเค•เคคी เคนैं, เคœैเคธे เคธाเคฅिเคฏों เค•े เคธाเคฅ เคœुเคก़े เคฐเคนเคจा, เค†เคจंเคฆเคฆाเคฏเค• เค—เคคिเคตिเคงिเคฏों เคฎें เคถाเคฎिเคฒ เคนोเคจा เค”เคฐ เคชेเคถेเคตเคฐ เคฎเคฆเคฆ เคฎाँเค—เคจा।


เคฐเคšเคจाเค•ाเคฐों เค”เคฐ เคฏुเคตाเค“ं เคฎें เค…เคชเคฐाเคงเคฌोเคง

เคฎเคนाเคฎाเคฐी เค•े เค•ाเคฐเคฃ เค…เคชเคฐाเคงเคฌोเคง เค•ा เค…เคจुเคญเคต เค•เคฐเคจे เคตाเคฒे เคฏुเคตाเค“ं เค•ी เคธंเค–्เคฏा เคฎें เคญी เคตृเคฆ्เคงि เคนुเคˆ เคนै। เคฏुเคตाเค“ं เคฎें เค…เคชเคฐाเคงเคฌोเคง เค•เคˆ เค•ाเคฐเค•ों เค•े เค•ाเคฐเคฃ เคนो เคธเค•เคคा เคนै


 #imageconsulting #leadershippresence #leader #communication #corporate #bodylanguage #nonverbal #voice #presentation #leadership #success #personalbrand #coaching #selfconfidence #boostselfconfidence #networking 

#imageconsultant #imageconsulting #leadershippresence #leader #communication #corporate #bodylanguage #nonverbal #voice #presentation #leadership #success #personalbrand #coaching #selfconfidence #boostselfconfidence #networking